The Trifecta: Empowering People through the Power of AI

Augment Intelligence

Together, AI and IA power innovations in healthcare:

Healthcare service providers will collaboratively and proactively manage population health, monitor disease status, provide at home acute care treatment, and maintain continuous communications with patients and caregivers.

Patients and clinicians will work together to achieve improved health outcomes through coordination of care, health literacy, sharing of pertinent data and records, and continuous tracking of patient health indicators.

Life sciences companies will enhance decision-making to improve product safety. FDA records of adverse drug reactions can be mined to identify pairs of medications that seem to cause problems when taken together.

Together, AI and IA power innovations in healthcare:

Healthcare service providers will collaboratively and proactively manage population health, monitor disease status, provide at home acute care treatment, and maintain continuous communications with patients and caregivers.

Patients and clinicians will work together to achieve improved health outcomes through coordination of care, health literacy, sharing of pertinent data and records, and continuous tracking of patient health indicators.

Life sciences companies will enhance decision-making to improve product safety. FDA records of adverse drug reactions can be mined to identify pairs of medications that seem to cause problems when taken together.

80% of doctor’s current activities will be replaced in the future by intelligent systems:

Diagnostic tests and procedures will be automatically ordered, medications will be prescribed, digital therapeutics will be recommended, and prior authorizations will be instantly approved.

Healthcare patients will receive better healthcare management when behavioral economics are applied to understand their needs.

How Philips is embedding analytics into all its business markets & functions

Featured Solutions

External data rating modifier for a payer

With an innovative analytical framework applied on external data, payers can enhance the performance of existing rating modifiers to inform additional risk. Health insurers can leverage new signals from consumer data to predict claims experience to deliver an improved risk assessment process. These new signals include factors indicating buying behavior patterns, socio economic and financial statuses and health interests.

The enhanced rating modifier can help payers create an R-squared lift of up to 15%.

This lift is over and above claims experience typically informed by internal risk factors that payers already assess—such as age, gender, and location.

A few external indicators of additional risk informed by claims experience can include data on economic stability, usage of mobile phones, prime time television usage, smoking, community engagements, derogatory records, and dwelling status.

Claims anomaly detection for a payer

It’s time for payers to experience a better way to identify anomalous claims. The common process to identify anomalies is business-rules-driven, manual intensive, applied in a post-pay scenario and focuses mainly on known patterns, thus solving the problem partially.

Get better results by:

Creating a visual solution suite to help identify anomalies, track alerts, and measure the impact of interventions

Delivering significant impact in both post-pay and pre-pay scenarios

The significant ROI in initial year/s enables payers to self-fund a suite of more advanced AI-driven scalable solutions to keep identifying and tracking anomalies, and improving recoveries from the flagged claims.

Case Studies

3 min. read

Reduce high costs of care associated with avoidable ER visits

The Big Picture The high cost of maintenance and limited availability of Emergency Rooms (ER) facilities are under intense scrutiny by payers, the government, providers and employers. According to the Centers for...

Improve collectability of the self-pay portion of medical expenses

The Big Picture Escalating healthcare costs have forced employees with employer-provided insurance to bear a higher portion of self-payment costs such as co-pay, coinsurance, deductible and out-of-pocket expenses....

Develop prediction framework to address high attrition

The Big Picture Wholesale drug distributors have experienced strong competition and consolidation leaving only a few surviving entities to service most of the US market. A leading distributor of drugs to long-term care...

The Big Picture Non-adherence of medication is one of the most critical problems when treating patients with chronic conditions. Patients who do not follow the prescribed drug regimen are more likely to suffer poor...

Leverage external data to improve pricing and underwriting decisions

The Big Picture A leading health insurer believed it could better predict claims experiences using external data, as supplement to internal claims data. The organization wanted to leverage the predicted claims...

Improve claims anomaly identification and tracking

A payer identifies $5M+ in potential savings in first year of powering claims anomaly identification with analytics

The Big Picture A top 5 US payer wanted to improve its ability to identify and track claims anomalies. Its existing process was business rules-driven, significantly manual, applied only in a post pay scenario and lacked...

The Big Picture: A leading pharmaceutical company was facing a decline in the sales volume of its flagship drug, which usually accounts for over $5 Billion of its annual sales. Less than 30 percent of physicians...

Top 5 US health payer identifies $45M in overpaid claims

The Big Picture: The US healthcare system loses more than $200 billion every year in fraud, waste, and abuse-nearly 10 percent of annual healthcare spending. The Government Accountability Office (GAO) has deemed...